透明度(行为)
医学
随机对照试验
可解释性
心理干预
梅德林
背景(考古学)
描述性统计
循证医学
临床试验
物理疗法
外科
替代医学
统计
计算机科学
内科学
护理部
政治学
古生物学
法学
病理
机器学习
生物
计算机安全
数学
作者
D. Waller,Josh Saurino,Adam Khan,Taylor Gardner,Alec Young,Chance Bratten,Eli Paul,Bryan Dunford,Will Roberts,Aaron Relic,Alicia Ito Ford,Matt Vassar
标识
DOI:10.1136/rapm-2025-107065
摘要
Background Regional anesthesia (RA) is central to multimodal analgesia, yet many supporting randomized controlled trials (RCTs) may lack the rigor needed for evidence-based block selection. Objectives To evaluate the clinical usefulness and transparency of RCTs investigating RA interventions for lower extremity surgeries, using the van ’t Hooft et al framework. Methods Embase/MEDLINE were searched for RCTs (2014–2024) examining RA interventions for lower-extremity surgery. Data were extracted in duplicate using clinical-utility and transparency criteria. Analyses included descriptive statistics, linear regression for temporal trends, Pearson correlation, and multivariable regression to identify predictors of usefulness. Results Among 248 RCTs, patient-centeredness was universal, while feasibility (77.0%) and context placement (77.4%) were common. Pragmatism (2.0%) and value-for-money analyses (0%) were rare. Transparency varied: conflicts of interest were disclosed in 88.7%, pre-registration occurred in 39.9%, public protocols in 10.1%, and raw-data sharing in 1.2%. Transparency improved over time, correlated with clinical-utility scores (r=0.32, p<0.001) and was greater in hospital-funded, self-funded, and higher-impact journals. Limitations Usefulness scoring involves subjective judgment; non-English trials were excluded; the absence of formal risk of bias analysis limits interpretability of trial quality. Discussions/conclusions Although transparency is improving, most trials remain insufficiently pragmatic, lack economic evaluation, and rarely share data, limiting real-world applicability. The results of this study suggest that aligning funder, journal, and collaborative expectations around open science and pragmatic design could accelerate the generation of high-utility evidence for perioperative block selection.
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